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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch

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Crypto M - Crypto News

@CryptoM · Post #64774 · 04/09/2026, 10:01 PM

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🚀 Bank of Korea Advocates Bank-Led Model for Won Stablecoins The Bank of Korea has proposed a bank-led model for issuing won stablecoins, citing media ownership laws as justification. According to NS3.AI, the central bank suggests that issuers should adhere to a rule requiring banks to hold 50% plus one share ownership. This proposal was detailed in materials submitted to Democratic Party lawmaker Park Min-gyu's office, referencing Article 8 of the Broadcasting Act and Article 18 of the Newspaper Act. However, critics argue that using media ownership laws to regulate stablecoins represents a significant logical leap. #BankofKorea#Stablecoins#WonStablecoins#BankLedModel#MediaOwnershipLaws#NS3AI#DemocraticParty#ParkMinGyu#BroadcastingAct#NewspaperAct#Criticism

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